To appear in Evolutionary Programming V: Proceedings of the Fifth Annual Conference on Evolutionary Programming, Cambridge,
MA: The MIT Press. 1996.
Symbionticism and Complex Adaptive Systems I:
Implications of Having Symbiosis Occur in Nature
Jason M. Daida, Catherine S. Grasso, Stephen A. Stanhope, and Steven J. Ross
The University of Michigan
Artificial Intelligence Laboratory and the Space Physics Research Laboratory
2455 Hayward Avenue, Ann Arbor, Michigan 48109-2143 USA
(313) 747-4581 work, (313) 764-5137 fax, [email protected]
Abstract
Over the past several years, there has been an
increasing interest in the biological phenomena of
symbiosis by those in complex adaptive systems and
evolutionary computation. We describe in this
paper some of the caveats involved in modeling or
using biological symbiosis as a computational
metaphor. We specifically consider some of the
common philosophical viewpoints on symbiosis and
comment on the appropriateness of these viewpoints
for use in complex adaptive systems and
evolutionary computation.
1. Introduction
1.1 Background
Nature—as the saying goes—is red in tooth and claw, in
part because of the natural selection. A key principle of
evolutionary biology and Neo-Darwinism, natural selection
has evoked themes of struggle, survival, competition, and
warfare. Nature is not a benign place—it is a “jungle” out
there—and given any of its recent metaphors, nature is not
ordered according to the weak, but to the strong.
In nature, symbiosis occurs. Symbiosis—as initially defined
in 1879 by Anton de Bary—involves the living together of
organisms from different species.1 Occasionally, such life
together results in detriment to one of the partner species, as
in parasitism. The larger struggles implicit in nature become
reflected in the smaller struggles that occur in close quarters
between parasitic symbionts and hosts. From this perspective,
symbiosis mirrors the “redness” of nature.
Occasionally, however, such life together results in
cooperation: as in commensalism, when only one species
benefits without a significant effect on its partner species; or as
in mutualism, when both partner species benefit. The
altruistic outcome seems anomalous in either case. Yet at the
risk of over-dramatization, one could explain such cooperative
symbioses as that of strange bedfellows arising out of
extenuating circumstances In that sense, “weak” species can
gain an advantage by forging alliances and creating a synergy
of complementary strengths to subdue a common adversary. If
such wartime logic was appropriate, these alliances-of-necessity
would likely be fleeting, and the struggle for survival would
return as the norm upon disappearance of a common foe.
1
Zusammenleben ungleichnamiger Organismen. [16]
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Although the “redness” of nature can yield a picture that
illuminates symbiosis, is it a correct description? Is symbiosis
no more than an aspect of natural selection? This paper
explores the implications of having symbiosis occur in nature
and the ramifications of those implications in studies involving
complex adaptive systems and evolutionary computation.
1.2 Brief Terminology
Throughout this paper, we use the following definitions,
unless otherwise noted:
Symbiosis. Relationships that are constant and intimate
between dissimilar species. Note that by “constant and
intimate,” we exclude purely ecological interactions. By
“species,” we include organisms and microbial life forms (e.g.,
protoctists and bacteria).
As in [76], we denote symbiosis as inclusive of mutualism,
commensalism, and parasitism. These three terms have been
commonly used to classify types of symbiosis and presume that
a symbiotic partnership can be measured in a cost-benefit
framework. In particular, these terms have usually denoted the
following: a mutualistic symbiosis 2 describes a relationship in
which all organisms involved derive benefit; a commensalism,
a symbiosis in which one organism benefits without any other
apparent benefit or cost to the other members of the
association; and a parasitic symbiosis3, a relationship in which
one organism benefits at the cost to the other members.
Symbionticism. A class of theories that focuses on symbiosis
as an evolutionary process (e.g., [51, 84]).
1.3 Overall Problem Statement
Unlike natural selection, the role and functionality of
symbiosis is still a contested topic that does not have an overall
consensus within the communities of the biological sciences.
Part of this lack of consensus stems from an inadequate
theoretical treatment of symbiosis. Another part of this lack of
consensus stems not so much from science discourse than with
philosophical outlook. Conflicting interpretations of available
empirical evidence—from paleontological records to field
observations to laboratory experiments—also plays a role in
2
We do make a distinction between mutualism and mutualistic
symbioses. Mutualism describes any relationship between dissimilar
species that involve cooperation, regardless of the duration of that
relationship. A mutualistic symbiosis is a type of mutualism that
involves a prolonged and intimate association between all members.
3
We make a similar distinction between parasitism and parasitic
symbioses.
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Symbionticism and Complex Adaptive Systems I
this lack of consensus. Subsequently, many of the
communities in the biological sciences have been divided into
several camps on this topic. These camps include those who
believe that symbiosis
• represents no significance to evolution (which may likely
represent the majority opinion in evolutionary biology).
• represents a rare accident that may have once resulted in
something significant, but has not amounted to anything
since then.
• represents a significant evolutionary force.
◆
In the fields of complex adaptive systems and evolutionary
computation, a growing minority of researchers have been
borrowing metaphors from research in symbiosis. We concur
that although the idea of symbioses is germane to work in
these fields, there exist significant caveats either in adopting
symbiosis as a computational metaphor or in modeling
symbiosis as an aspect of complex adaptive systems. We
contend that comparisons between various models of
symbiosis in evolution does require an awareness of the
philosophy behind each model. We further contend that
contributions to evolutionary biology given a particular
symbiosis model can be compromised if attention is not paid
to the philosophical source of each metaphor. Finally, we
contend that minor modifications in a definition of symbioses
could have broad and far reaching ramifications for theoretical
and evolutionary biology, as well as for complex adaptive
systems and evolutionary computation.
The purpose of this paper is to focus on a part of this
problem statement. We specifically concentrate on the
meaning (i.e., role and functionality) of symbiosis in
theoretical biology. We then compare those meanings with the
phenomena of symbiosis as it occurs in the here and now (as
opposed to including symbioses from other ages). In
particular, in Section 2, we examine some of the previous work
in complex adaptive systems and evolutionary computation.
We examine in Section 3 how the meaning of symbiosis does
change depending on a person’s philosophical viewpoint and
how some of these meanings are not always grounded in the
actual phenomena. In Section 4, we suggest a viewpoint that
would be suitable for work in complex adaptive systems and
evolutionary computation. We leave for another paper the
ramifications of symbiosis in an evolutionary context.
2.0 Brief Survey of Previous Work
Several themes in complex adaptive systems and
evolutionary computation that feature symbiosis have
appeared in the literature over the past several years. These
themes have included:
• investigating fundamental roles of symbiosis in evolution
by modeling symbiont-host interactions.
• broadening the first theme by modeling symbiosis in the
context of evolving ecosystems, which include several other
types of interaction.
• treating symbiosis as a metaphor for computation and
crafting algorithms accordingly to solve problems in
engineering and technology.
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Daida et al.
• in an almost separate tradition, investigating either the
fundamental role of parasitism in evolution or treating
parasitism as a metaphor for computation.
• investigating viruses—mostly as a metaphor for
computation and mostly in a context separate from
aforementioned themes of symbiosis and parasitism.
(Although viruses are not usually considered organisms, the
current distinction between computational “viruses” and
“parasites” is ambiguous and arbitrary.)
• investigating and adopting as computational metaphors
other biological phenomena that researchers have
considered symbiosis, but technically fall outside of de
Bary’s definition.
The following paragraphs survey the work under each
theme. Note that even in this cursory survey that symbiosis is
not evenly treated and that isolated traditions have already
occurred depending on what aspect of symbiosis is being
described. Although this treatment is not by itself noteworthy,
we have been concerned with a growing tendency for
researchers to claim that the essence of symbiosis is being
modeled, without recognizing that there are aspects of
symbiosis that have not been necessarily considered in their
formulation.
A few papers have focused on investigating the
fundamental role of symbiosis by modeling symbiont-host
interactions. Many of these papers have subsequently
concentrated on the co-evolutionary aspect of symbiosis,
including [6, 64]. This particular focus on co-evolution often
involves Valen’s hypothesis of the Red-Queen’s Race4 [81].
Several papers have broadened the first theme by studying
symbiosis in the context of artificial computational ecologies.
These ecologies are not usually premised on symbiosis alone
and can usually demonstrate other types of interaction (e.g.,
predatory-prey). This includes Holland’s Echo [32, 33],
Skipper’s Zoo [75], and Taylor’s RAM [78]. Of these
approaches, only RAM has been used by biologists to model a
specific animal-plant system.5
While investigation of the fundamental roles of symbiosis
can offer insight regarding the place of symbiosis in evolution,
others have sought to leverage principles gleaned from
biological symbiosis by applying such principles to solve
engineering problems. A few of these works are theoretical in
nature (e.g., [14]). Some works focus on developing a
computational analog for a particular aspect of symbiosis (e.g.,
[73]). Other works describe a symbiotic algorithm (e.g., [67])
or describe other algorithms that have embedded in them
abstracted principles of symbiosis (e.g., [7], [13]).
In an almost separate tradition, a significant body of work
has focused on parasitism. Those who have investigated
parasitism do not necessarily contend that any other aspect of
symbiosis is of significance in evolution. This body of work
includes fundamental investigations, as in Ikegami and
Kaneko’s [35] work on parasites and co-evolution, Maley’s
[49] work on virulence modeling, or as in work featuring
4
The Red Queen’s Race alludes to a game in L. Carroll’s story
Through the Looking Glass that required contestants to run just to stay
in place.
5
A Hydra/Chlorella symbiosis was modeled [61, 79]. See also the
computer simulation by [59].
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Symbionticism and Complex Adaptive Systems I
computational ecologies such as TIERRA [70], EVOLVE [65]
and BABEL [72] represent other models of parasites. Of these,
TIERRA is arguably the most well known. Another
computational ecology, DARWIN, is possibly the oldest
artificial ecology that pre-dates TIERRA and Core Wars. One
of DARWIN’s “famous” inhabitants was a parasite. (See
popular accounts in [18] and [44].) On a separate note, work
concerning this tradition includes treatment of parasitism as a
means of fostering robustness in engineering solutions. Of
these, Hillis’s [31, 30] work has been often mentioned.
Also as a separate tradition, another body of work has
focused on viruses. (Viruses are not usually considered
organisms and subsequently are not classified as being
symbiotic. Still, the mechanisms that determine infection and
reproduction in computer viruses have much in common with
biological parasites. For example, the difference between a
TIERRA parasite and a computer virus is moot.) Those who
have investigated viruses do not necessarily contend that it has
anything to do with either symbiosis or evolution. Key works
concerning viruses include Cohen’s dissertation [10], and
subsequent discussions [17, 77] of computer viruses as a form
of artificial life. Not surprisingly, there has been discussion of
developing biologically inspired immune systems for
computers [41].
Finally, investigating and adopting as computational
metaphors other biological phenomena that researchers have
considered symbiosis, but technically fall outside of de Bary’s
definition. Using an unusual sense of the term parasitism,
Toquenaga [80] has described “information” parasitism. Other
investigators have used a somewhat relaxed definition of
symbiosis. For example, Ono [66] has designed a “symbiotic”
computational ecology that models bees and flowering plants 6.
(Ono defines symbiosis as tantamount to mutualism).
Furthermore, others have relaxed de Bary’s definition by
extending his definition to include interactions that treat
organic molecules as either host or symbiont.7 Such work
includes Wong’s [86] simulations of prebiotic molecules, and
Boerlijst’s [2, 3] work in hypercycles and prebiotic molecules.
3. Symbiosis and Biology
In further understanding symbiosis in the context of
complex adaptive systems and evolutionary computation, we
need to consider the phenomenology of symbiosis in the
context of the biological sciences. The biological sciences
provide, among other things, abstractions of biological
phenomena that can be adopted for use in evolutionary
computation and complex adaptive systems. However, even
the most objective of these abstractions can often contain
biases. Such biases depend on a number of factors, ranging
from the nomenclature and conventions in a given subfield to
philosophical constraints for a given belief system.
Normally, such biases are fairly transparent within
subfields, in which nomenclature, convention, practice, and
6
Technically, bees and flowering plants have a mutualistic
relationship, but not a symbiotic one because individual bees do not
live together in intimate association with an individual plant.
7
This extension to de Bary’s definition has also occurred in the
biological sciences. See [63].
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Daida et al.
philosophy are usually complementary to each other. Such
complementariness is not easily the case with symbiosis. This
section describes some of the difficulties in describing
symbiosis in the biological sciences.
3.1 Symbiosis in Theoretical Biology
What is symbiosis? What are the consequences of being in
symbiosis?
From a qualitative perspective, de Bary’s definition is
descriptive and sufficient for many subdisciplines in the
biological sciences. In particular, his definition allows one to
identify what is and what is not in symbiosis. For example,
under de Bary’s definition, legumes and the nitrogen-fixing
bacteria that inhabit their roots are in symbiosis; rabbits and
the foxes that prey on them are not. From a theoretical
perspective, however, de Bary’s definition allows room for
interpretation. Unlike natural selection, which points to a
sifting mechanism, mutation, which points to a change
mechanism, and genetic crossover, which points to another
type of change mechanism, symbiosis points to a type of
relationship. Mechanisms are amenable to a functional
notational description—i.e., a mathematical operator;
relationships, on the other hand, are not so easily abstracted.
Relationships can either be defined in terms of states or
operators. For example, a marriage relationship has
traditionally been referred to as a state (as in, “a state of being
married,” which in some cultures would follow “a state of
being in love”). In contrast, some judicial courts recognize
common-law marriages, which uses an operational definition,
i.e., “co-habitating together.” Although there exists a
substantial amount of overlap in either state or operation
between traditional and common-law marriages, the two
definitions are not equivalent—at least according to more than
a few parents. Consequently, depending on what one believes
that symbiosis is, one presupposes either of the following
underlying questions. If one sees symbiosis as a state, one asks
the question “What are the characteristics that distinguish
symbiosis from any other type of relationship?” If one sees
symbiosis as an operator, one asks “What are the implicit
mechanisms (operators) that determine a symbiotic
relationship?”
Although much of the work in symbiosis has emphasized
symbiosis as a state, 8 both underlying questions have been
addressed in theoretical biology9 at one time or another, For
example, much of the early work from around 1935 features
lumped-parameter models (usually Lotka-Volterra), which
consists of systems of differential equations that describe
logistics (populations) of interacting species. (See [4, 12, 85].)
Traditionally, in the lumped-parameter models, species
interact by competing with or preying upon each other. It is
possible, however, to model a “state of cooperation” by
8
We have ommitted mention of many of the work that examines
symbiosis, but does not necessarily contribute to complex adaptive
systems, artificial life, and evolutionary computation. Much of that
work is specific to biology (as in the MacArthur-Wilson Model in
[12]) or to a particular symbiotic system (e.g., [68]).
9
For the purposes of this paper, we use the term theoretical biology
to encompass mathematical and computational work in ecology,
population, population genetics, and evolution.
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Symbionticism and Complex Adaptive Systems I
reversing the arithmetic signs of a model’s integration
coefficients.10 Note that this state does not map directly into
de Bary’s definition of symbiosis. In other words, this state
includes non-symbiotic mutualisms, but excludes other aspects
of de Bary’s symbiosis (e.g., parasitism). In a sense, what
becomes interesting about symbiosis is not so much that
organisms live together, but rather that they cooperate. 11 Not
surprisingly over the years, some biologists have come to
regard “symbiosis” as being tantamount to “mutualism.”12
There are some recent theoretical works that have
considered symbiosis an operator or set of operators. Works by
Maynard Smith [56, 57] abstracts symbiosis in terms general
enough for research in complex adaptive systems and
evolutionary computation. He has regarded symbiosis as an
evolutionary mechanism for increasing complexity by way of
compartmentalization of genomes from different species,
followed by synchronized replication of those genomes.
In at least three different ways, Maynard Smith and
others 13 have departed from the conventional wisdom by
treating symbiosis as a kind of operator. First, they have
extended de Bary’s definition to include all organic forms—
not just organisms—that employ operators associated with
symbiosis. This extension would then include non-organismic
entities such as viruses, plasmids (circular strands of
extrachromosomal DNA), and viroids (naked strands of
RNA). (See [63].) Second, they have decoupled the meaning
between “mutualism” and “symbiosis.” Not only is mutualism
considered distinct from symbiosis, but some have posited that
merely “living together” does not necessarily result in
mutualism (e.g., [20]). Third, they consider the cost-benefit
terms that characterize the kinds of interaction between
symbionts and hosts—i.e., mutualism, commensalism, and
parasitism—as sufficient but not necessary properties in
describing symbiosis. Ultimately, what is of interest is not that
a relationship is mutualistic (or parasitic, or commensal), but
in the operations and the use of those operators that enable
dissimilar species to intimately associate with each other over
evolutionary significant durations.14
◆
We can mention a few other differences between the
viewpoints of symbiosis as state or operator. One difference is
in the treatment of time scales. Lumped-parameter (LotkaVolterra) models developed under a symbiosis-as-state
10
Even though operators were involved, symbiosis was still treated
as a state and not as an operator. If instead an operater was to have
been emphasized, a parameter list would have needed to have been
specified—i.e., causality would have needed to be established within a
given model, rather than being established arbritrarily from the
person specifying the model.
11
For example, Wolin subsumes symbiosis under mutualism—
e.g., “The duration and intimacy of association also varies between
interactions: some mutualists are symbiotic, that is, live together,
while others are free-living.” ([85], p. 249)
12
For example, Dawkins succinctly states, “A relationship of
mutual benefit between members of different species is called
mutualism or symbiosis.” ([15], p. 181)
13
Like [27], which presents a case for symbioses being another
type of mutation. Note that, although the author is not a theoretical
biologist, per se, his paper is theoretical in scope.
14
Also referred to as evolutionary stable strategies. See [58].
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Daida et al.
viewpoint often hold constant or ignore those conditions and
mechanisms normally associated with evolutionary change
(e.g., natural selection). Although one could extend the
conclusions drawn from such models to evolution, such
models are more appropriately used to describe interactions
over ecologically significant time scales. On the other hand,
Models developed under a symbiosis-as-operator viewpoint
have concentrated more on the processes that operate on
evolutionary significant time scales.15
Another, perhaps more significant difference is the
treatment of the cost-benefit properties of symbiosis as
deterministic rather than emergent, corresponding to
symbiosis-as-state and symbiosis-as-operator viewpoints,
respectively. The distinction between deterministic and
emergent treatments can be illustrated in how one describes a
cost-benefit property—say, mutualism. If one considers
mutualism to be a deterministic property for symbiosis to
occur, one would likely believe that a need for members to
cooperate is what drives them to cooperate. Game theoretic
descriptions of cooperation and defections would then apply,
as mutualism becomes just one of several strategies between
interacting members. In that sense, by adopting a strategy of
alliances, “weak” species can gain an advantage to subdue a
common adversary or to live in an otherwise hostile
environment. If, on the other hand, one considers mutualism
to be an emergent property, one would likely believe that
cooperation is a by-product of interaction. Members can
interact by chance or by need, but singly taken, each low-level
interaction between members (e.g., an exchange of nutrients)
would not necessarily have an intrinsic cost-benefit value. In
that sense, species could continue to remain in symbiosis
regardless of cost-benefit outcome.
◆
We mentioned earlier that there appears to be an almost
separate tradition in complex adaptive systems and
evolutionary computation of treating parasitism as a theme
distinct from symbiosis. Not surprisingly, this situation
mirrors what has happened in the biological sciences.
There exists a sizable community of biologists that has
treated parasitic associations as distinct from symbiosis (as
noted in [19]). This distinction has appeared implicitly in
their works as tacit omissions of symbiosis. In theoretical
biology, such works include [43, 55], which highlights the
disease aspect of parasitism; [54], which challenges
conventional wisdom on the evolution of virulence; and [25,
26], which discuss the role of parasitism in the evolution of
sex. This distinction has also appeared explicitly, as in [15],
which treats parasitism and “symbiosis” (though “mutualism”
was meant) as separate cases in evolution.
15
Nonetheless, we do note that the time-scale differences between
these current tendencies—for symbiosis-as-state models to emphasize
ecologically significant time scales versus symbiosis-as-operator
models to emphasize evolutionary signficant time scales—might
eventually be moot. In particular, individual-based models (e.g.,
cellular-automata simulations) can and have been increasingly used to
support either viewpoint.
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Symbionticism and Complex Adaptive Systems I
Given that nearly all parasites live in close association with
their hosts,16 this distinction is a consequence of treating
symbiosis as a state. As in the case of mutualism, where some
have regarded the state of cooperation as paramount, in the
case of parasitism, some have regarded the state of disease as
paramount. In considering the state of disease as paramount,
one could augment the de Bary’s scope of parasitism to
include non-organisms like viruses. We can see this
augmentation in works like [54], which broadly defines
parasites to include “viruses, bacteria and protozoa’s along
with the more conventionally defined helminth and arthropod
parasites.” If one then further considers that disease is a state
that afflicts humans, one can intuitively understand why it is
disease and not symbiosis that receives a lion’s share of
attention in the larger context of the biological (medical)
sciences.
3.2 The Biology of Symbiosis
What is symbiosis? What are the consequences of being in
symbiosis?
In theory, according to the previous section, symbiosis is a
type of relationship that describes a protracted and intimate
association between dissimilar species, which subsequently can
be abstracted in terms of either a state or operator. To address
which of these viewpoints (state or operator) is the more
appropriate of the two, we need to consider how symbiosis
occurs in nature—the biology of symbiosis. Therefore in
considering the biology of symbiosis, we ask two further
questions:
Where does one look in nature? What does one find?
Although these questions may seem fairly straightforward,
the answers are not.. The primary confound here lies in the
large variety of symbiotic systems that can be found in nature.
Where does one look in nature?
When we consider where to look in nature for symbiosis, a
few examples may come to mind. For instance, we may think
of small fish that clean the mouths of larger carnivorous fish.
Others may think of lichens, which is an association between
unicellular plants and fungus. Others may also think of
particular plants, like soybeans, which use bacteria in their
roots to help “breathe” nitrogen. While all of these examples
fall under de Bary’s definition of symbiosis, they do not by
themselves offer direction as to where to look in nature for the
phenomena.
Of course, we could also solicit another’s opinion on where
to look. However, when we do so, we need to recognize that
that person’s response is subject to philosophical bias. This is a
consequence of the fact that where one decides to look in
nature for symbiosis is dependent on what one expects of the
phenomena.
The following paragraphs briefly recapitulate an informal
cross-section of perspectives on symbiosis and subsequent
decisions as to where to find the phenomena.
16
There are some parasites that do not live in close association
with their hosts. For example, mosquitoes are to mammals as bees are
to flowers.
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1. Symbioses are relatively rare or as Keller states,
symbioses are nothing more than “special cases” ([40], 71).17
With this perspective, one could reasonably surmise that one
best looks for symbioses in the uncommon places.
We note that this perspective is usually associated with
those who treat symbiosis as a state of mutualism and who
believe that mutualism is the (rare) exception to natural
selection and competition.
2. “Symbiotic relationships…are common….” ([15]. p.
181). With this perspective, one could reasonably surmise that
one does not have to look too hard to find a symbiotic
association.
We note that this perspective has often been generally
associated with those who treat symbiosis as a state of
mutualism and who believe that mutualism is a general
phenomenon. (e.g., nature is instead “green in root and
flower.”). We further note that this perspective says little about
one’s view on the role of symbiosis in evolution.
We have noted another concurrent and complementary
perspective that prevails among biologists, but only mention it
briefly here because this perspective shares much in common
with those who see mutualism as a common phenomenon.
This perspective maintains that parasitic relationships are
common. This perspective has been associated with at least
two groups of biologists. One group treats symbiosis
(mutualism) as a state that is distinct from parasitism (another
state) and that parasitism is a general phenomenon. Another
group treats symbiosis as an evolutionary operator that is
distinct from symbiosis (mutualism) as a state. (Here the role
of parasitism is seen by some to provide a basis for
macroevolution For example, the strategy of sexual
reproduction could be a result of parasitism [25, 26]).
3. “Symbiosis…is a universal phenomenon. There are
practically no plants or animals free of symbionts living on or
in them.” ([69], p. 381) With this perspective, one could
reasonably surmise that wherever one finds organisms, one
would find evidence of a symbiotic association.
The conceptual jump from common to universal
phenomenon is nontrivial, especially if one does not relax de
Bary’s original definition.18 It would imply that every form of
life that we see on a day-to-day basis is likely to be in a
symbiotic association.
We note that this perspective is usually associated with
those who treat symbiosis as an operator or a class of operators.
The cost-benefit characteristics of mutualism or parasitism
17
In arguing that conpetitive interactions are the norm in the
natural world, Keller did entertain the alternative hypothesis of
symbiosis/mutualism, but also indicated that symbiosis/mutualism is
of little consequence. She said, “These, of course, are the kinds of
interactions that are generally categorized as special cases: ‘mutualist,’
‘cooperative,’ or ‘symbiotic.’ The view of these as special cases tends
to persist even in the most recent literature, where a new wave of
interest in mutualism can be detected among not only dissident but
even a few mainstream biologists.” ([40], p. 71).
18
A significant modification to de Bary’s definition has been to
relax the requirement of having the associations occur in close
proximity to each other. In this way some have extended the
definition of symbiosis to include ecological interactions. Usage of
this relaxed definition has also figured prominently in discussion of
the Gaia Hypothesis [48].
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Symbionticism and Complex Adaptive Systems I
that define much of what people expect to see is secondary in
importance to the kinds of interactions that occur during
symbiosis. It certainly becomes possible then, to have a
symbiotic relationship, even if the cost-benefit characterization
of that relationship remains ambiguous.
What does one find?
If one looks through the aforementioned perspectives, one
would likely find what one seeks. Symbioses do occur in rare,
seldom seen organisms. To be certain, symbiosis has been used
in many organisms as a source of novel metabolic capabilities,
which enables organisms to live in otherwise hostile and
extraordinary environments. One would have to travel to the
“far corners of the earth,” like the polar deserts or the ocean
floors, to find some of these organisms. And yet, this same
source of novel metabolic capabilities also allows organisms to
live in mundane surroundings. We could look no farther than
our backyard to find an organism in symbiosis.
The following paragraphs highlight two symbiotic species.
The first reinforces the notion that symbioses are rare, special
cases since these species are seldom seen and are found in
extremely inaccessible environments. The second reinforces
the notion that symbioses are common, even universal
phenomena because this species is well acquainted by most.
The first highlighted species lives on the ocean floor by
hydrothermal vents. Although these vents do warm an
otherwise cold environment, the environment in and around
these vents could be considered hostile to most life, especially
since these vents often release substantial amounts of sulfides
(including hydrogen sulfide19). Sulfides are highly toxic to
organisms with oxygen metabolisms, since these chemical
compounds usually block the ability of an organism to use
oxygen. It is in this environment that there can be found dense
and thriving communities of tube worms, as well as clams and
other organisms. A hydrothermal vent can serve as a kind of
ecological oasis in an otherwise sparsely populated ocean floor.
What is noteworthy about these tube worms and the other
organisms around these vents is that they have not substituted
the heat from hydrothermal vents for sunlight, but instead
have evolved sulfur-based (thiotrophic) metabolisms that are a
direct consequence of these organisms’ symbiosis with sulfuroxidizing (chemoautotrophic) bacteria. Indeed, a
hydrothermal vent tube worm (e.g., Riftia pachyptila) can grow
up to several feet long and is thought to derive most of its
nutrients, as well as its ability to metabolize hydrogen sulfide,
from symbiotic bacteria that live in what would otherwise be
its gut. [83]
The second highlighted species is us—i.e., Homo sapiens.
Intuitively, we do not seem symbiotic with anything else—at
least not in de Bary’s sense. We do not seem to live in
prolonged and intimate contact with other organisms (at least
we try not too). We derive our nutritional and metabolic
needs from the foods we eat and the air we breathe, instead of
relying on a symbiotic association to furnish these needs. Still,
symbiosis is very much a part of the human existence. In
particular, humans remain in symbiosis with bacteria
throughout most of their lifetime. Some of these bacteria have
19
Hydrogen sulfide is a more poisonous than cyanide, a chemical
used in gas chambers. [11]
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Daida et al.
a known cost-benefit characterization; others do not. Many of
these bacteria live in the intestines. As Garrett has observed,
there are more bacteria (mostly Esherichia coli)per square inch
of intestinal lining than there are people in New York City.
[23]. We can appreciate the abundance of symbiotic bacteria
in an intestine by noting that a third of the solid matter of
human feces consists of bacteria.
◆
We can perceive symbiosis as being as rare as a tube worm
that lives on the ocean floor to being as familiar as a neighbor
across the street. However, regardless of the philosophical
constraints on one’s perception, the phenomena of symbiosis
occurs commonly, perhaps even universally in nature. The
very commonality of the phenomena of one organism living in
close and intimate association with another would suggest a
pervasiveness of the phenomena. We can gain an appreciation
of just how pervasive the phenomena is by considering the
kinds of symbioses that just one host can accommodate. To
illustrate this, we describe in the following paragraphs some of
the other symbiotic associations that affect people.
Admittedly, some of symbiotic associations that humans
experience are fairly exotic. Isak documents a mutualistic
symbiosis between aborigines in Africa and a species of bird
known as a honeyguide [36]. In this relationship, honeyguides
lead honey gatherers to bee hives, upon which the gathers
break into these hives to collect honey. The honeyguides later
exploit the damage that the gatherers did to the hives to gain
access to food.
Nonetheless, most of these other associations are fairly
common. Humans play host to a number of parasites ranging
from foot fungus to hair lice to fleas. Humans play host to an
even greater number of internal microbes, which are
responsible for the diseases like dysentery, tuberculosis, staph,
pneumonia, strep and cholera [23]. Still, many of us would
like to think of ourselves as relatively disease- and parasite-free.
Subsequently, although disease and parasitism may be
common, it is not a way of life for a number of people in
developed countries.
Even more pervasive associations involve only remnants or
other organisms by now. The prevailing hypothesis that
explains the origin of true nucleated cells (eukaryotes) is serial
endosymbiotic theory (SET), championed by Margulis[50]
[52]. That eukaryotes were the result of symbiotic associations
of early bacteria (prokaryotes, or cells with no nucleus) was not
a new idea (see [84]). However in the 1960s, Margulis
provided the first testable hypothesis to demonstrate this. A
large body of evidence now exists that validates SET. Humans,
of course, are eukaryotes.
◆
We observe in the above example that there are a number of
different types of symbiotic interactions. Some involve internal
interactions, like bacteria in human intestines. Some of these
interactions have seem to lead to and integration of genotypes,
as suggested in serial endosymbiotic theory. Others appear to
be purely behavioral, as in a honeyguide/honey gatherer
symbiosis. Each of these symbioses satisfies de Bary’s
definition, yet it becomes apparent that just one state or one
operation would be inadequate to describe symbiosis. Indeed,
if we e xamine an even broader range of symbiotic associations,
we would find a range of groupings that can be arranged
6
Symbionticism and Complex Adaptive Systems I
Endosymbiotic
Total
Integration
Organelle
Adoption
Plasmid
Adoption
Gene Transfer
Plastid
“Symbiosis”
Endonuclear
Daida et al.
Ecological Interaction
Ectosymbiotic
Attachment
Behavioral
Predator-Prey
Herbivore-Plant
Intracellular
Intercellular
Extracellular
Figure 1. Continuum of interaction between dissimilar species.
according to just how closely dissimilar species interact. In a
sense, there exists a continuum of interaction and physical
proximity for all associations—both ecological and symbiotic
Figure 1 shows this continuum, which ranges from behavioral
and ecological interactions (on one end) to total incorporation
of a symbiont’s genomic information into a host’s nucleic
DNA (on the other end).20 The following paragraphs highlight
some of the grouping shown in Figure 1. For further
information, we refer to [5, 19, 29, 28, 76].
There are two broad groupings of symbioses: those in
which a symbiont remains outside a host (ectosymbioses) and
those in which a symbiont lives mostly inside a host
(endosymbioses).
Behavioral Symbioses. This type of ectosymbiosis is
common between animal-animal systems and is usually
characterized by some form of specialized communication and
behavior. Examples are cleaning fish and their larger hosts
(e.g., predatory eels, sharks, sea anemone) [47, 53].
Attachment Symbioses. 21 This type of ectosymbiosis involves
a symbiont either permanently or semi-permanently attaching
itself to a host. Examples include epiphytes (plants that grow
on other plants as a parasite for light and sometimes for
nutrients: e.g., mistletoe) [74]. Sea anemones that ride on the
shells of hermit crabs are another.
Extracellular Symbiosis. This type of endosymbiosis consists
of symbionts that live within cavities internal to a host (e.g.,
like tapeworms) or between cells in host tissue. The latter type
of extracellular symbiosis is called intercellular symbiosis, as in
typified by some lichens [34].
Intracellular Symbioses. This type of endosymbiosis is
established by a remarkably similar set of processes over a
diverse range of systems [60, 61].The inhabiting symbiont
must enter a host cell, avoid digestion, preserve host-cell
functions essential to it, reproduce within the host cell, and
survive transit to host offspring. Examples include unicellular
algae living within animals [5] and human viral infections
[23]. Endonuclear symbiosis is a subtype of intracellular
symbiosis that describes those situations in which the
symbiont inhabits a host’s nucleus (e.g., [24]).
20
We should emphasize here that this continuum does not
represent a series of evolutionary stages by which genotypes are
integrated. All this continuum represents is the kinds of symbiotic
interactions that can be found in nature at present.
21
Both attachment and behaviorial symbiosis are our terms. All
the other terms are nomenclature in biology.
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Plastid Symbiosis (also called Keptoplasty). This type of
endosymbiosis refers to retention of only a symbiont’s plastids,
as opposed to whole symbionts [42]. Plastids refer to
specialized compartments within a cell and are to plant cells as
organs are to multicellular organisms. This type of symbiosis
includes marine organisms responsible for the “red tide” [45],
in addition to a few species of mollusks [9]. Many plastid
symbioses are unstable. The notable exceptions to unstable
plastid symbioses are the fairly stable associations concerning
the red-tide organisms, otherwise called a plastic species.
Gene Transfer . This term does not describe endosymbioses
per se, but instead denotes a class of transfer mechanisms of
genomic information between symbiotic partners [1]. Usually
the symbiosis is intracellular, but not necessarily a plastid or a
endonuclear symbiosis. Noteworthy exceptions are horizontal
transfers between bacteria species and at least one example
involving an extracellular parasite. Agents of such mechanisms
include episomes [8] and “promiscuous DNA” [22, 39].
Examples include the phenomena of rapid conferral of
multiple-drug (antibiotic) resistance to various bacteria species
(e.g., those species that cause staph, dysentery, cholera).
4. Consequences
Given the situation outlined in the previous section, one
can guess at the potential for confusion for researchers in
complex adaptive systems and evolutionary computation.
Current work in theoretical biology could suggest to some the
possibility of expressing one complex adaptive model or one
computational algorithm to capture all of symbiosis—either as
biological phenomena or as a computational metaphor—as an
achievable goal. An examination of the biology of symbiosis
would suggest otherwise.
Furthermore, current works in the biological sciences do
contain particular biases on viewing what symbiosis is,
particularly concerning whether symbiosis is a state or whether
it is an operator. These works do not always mention which
viewpoint of symbiosis is being employed. This could
potentially lead to situations in which a researcher in complex
adaptive systems or evolutionary computation borrows existing
concepts from both symbiosis-as-state and symbiosis-asoperator viewpoints without addressing what could amount to
mixing irreconcilable philosophical differences between these
viewpoints.
◆
Philosophical differences aside, there remains the matter of
deciding which of the two viewpoints are the most appropriate
for those in complex adaptive systems and evolutionary
computation. To address this matter, we highlight three other
cases of symbiosis. In all of these cases, the basic interactions
that come from living together in close and intimate contact
does not change. What does change are the cost-benefit states
of mutualism, commensalism, or parasitism.
Green Hydra . Hydra belong to the same class of organisms
that includes jellyfish and sea anemones. The term green hydra
refers to those species of hydra that are in symbiosis with algae
(usually a Chlorella species). These hydra (like other hydra
species) live in fresh water and prey on small planktonic
organisms (like daphnia). Green hydra may live with or
without their symbiont algae.
7
Symbionticism and Complex Adaptive Systems I
Experiments by Douglas and Smith [21] have shown that
green hydra with symbionts live significantly longer than those
without symbionts if there are no prey, provided that the
hydra have ample light (i.e., hydra benefit). The cost-benefit
characterization changes when green hydra are fed and live in
light. In this situation, the population of green hydra with
symbionts i ncreases at nearly the same rate as green hydra
without symbionts (i.e., no apparent benefit). The cost-benefit
characterization changes again when green hydra are fed and
live in the dark. In this last case, the green hydra with
symbionts grows significantly slower than the green hydra
without symbionts (i.e., hydra are harmed).
Legumes and Bacteria Symbiosis. Legumes encompass many
of the species that are cultivated for food (i.e., bean crops).
Most legumes live in symbiosis with rhizobia bacteria, which
inhabit specialized structures (nodules) that form on the roots
of legumes.
It is well known that rhizobia bacteria enable legumes to
use the nitrogen in the air, rather than relying on the nitrogen
compounds that come with rich soils. (See, for example [46,
62, 82].)This, in turn, allows the legumes to grow in fairly
poor soils (i.e., legumes benefit). However, certain symbiotic
bacteria can turn parasitic if the soil becomes deficient in
boron (i.e., legumes are harmed).
Amoebae and x-Bacteria. The particular organisms involved
are what has been an amoebae species (i.e., the D strain of
Amoeba proteus) and x-bacteria, which are an unknown species
of bacteria that are rod-shaped and Gram-negative.
Jeon [38, 37] reports that a number of D strain Amoeba
proteus became infected with x-bacteria in 1966. Most of the
newly infected amoebae died (i.e., amoebae are harmed).
However, some of the amoebae survived. In several years, the
descendants of the originally infected amoebae have
subsequently become dependent on having x-bacterial to
survive (even though the cost-benefit to the amoebae is neither
a direct benefit nor harm). Furthermore, the new strain now
has a distinctly different cellular character than the original D
strain. The differences are great enough that there is
compelling evidence to support the claim that this symbiotic
strain of Amoeba proteus constitutes a new species.
In each of these three cases, the fundamental symbiotic
association has not changed, but instead the cost-benefit
characterization has. Further examination of highlighted
cases—particularly the green hydra and the legume cases—
would indicate that the low-level primary interactions between
host and symbiont have not been radically altered even when
the overall cost-benefit characterization changes. Even in the
third case, where the organisms have likely changed the nature
of their interactions, the cost-benefit characterization normally
cited as the reason for establishing a symbiotic association is
not readily apparent. In particular, it is one thing for an
organism to develop a tolerance or an infectious species to
become less virulent. It is quite another thing for a host species
to co-opt another so that the co-opted species become as a
kind of organelle. All three cases collectively refute the claim
that a particular cost-benefit characterization is intrinsic to a
symbiotic association. All three cases collectively support the
contention that the cost-benefit characterizations are
emergent, rather than deterministic properties.
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Daida et al.
A sample consisting of three cases does not by itself validate
the viewpoint of symbiosis-as-operator—it only suggests that
this viewpoint is so. We subsequently point out that the
validity of the viewpoint of symbiosis-as-operator has been
recently addressed by several biologists in greater detail than is
afforded in this paper. To mention a few, we note that Reisser
has preferred a functional (operational) definition [71] to
accommodate changes in ultrastructure, physiology, or
genetics. Douglas [19] has contended that what is paramount
in symbiotic associations are not cost-benefit states, but
interactions (operations). Margulis [51] has championed the
view that symbiosis is a source of evolutionary innovation; that
symbiosis is a kind of operator that is equal in significance to
natural selection.
5 Conclusions
This paper has addressed some of the issues at large in
integrating the concept of symbiosis into the fields of complex
adaptive systems and evolutionary computation. We have
noted some of the caveats involved in borrowing metaphors
from the biological sciences when concerning these
phenomena. We have indicated the potential for confusion if
care is not taken in understanding.
This particular paper has concentrated mostly on symbiosis
as it occurs presently in nature, rather than symbiosis as it
occurs in the context of evolution. We have shown that some
of the issues that concern us involve the questions having to do
with “what is symbiosis?” and “what are the consequences of
being in symbiosis?” We have attempted to show the ubiquity
of the phenomena; that symbiosis is not restricted to special
and rare cases, but instead germane to much of life. We have
also attempted to show that there are at least two distinct ways
in which to view symbiosis—as a state or as an operator—and
that these viewpoints are pervasive in the biological sciences.
We have contended that at least for complex adaptive systems
and evolutionary computation, the more appropriate view is
that symbiosis is a kind of operator.
Although we have not in this paper addressed the question
“Is symbiosis no more than an aspect of natural selection?” we
have established a foundation for which the two can be
compared. We have left for another paper the implications of
having symbiosis occur in the context of evolution. ■
Acknowledgments
The authors thank the conference organizers for inviting us
to deliver this paper. We gratefully acknowledge the following
individuals for the correspondence and dialogue that have
helped to shape the biological sciences discussion of this paper:
C.A. Bloch, F.L. Bookstein, L.R. McCloskey, M.J. McFallNgai, L. Margulis, E.G. Ruby, P.W. Webb, and R.E. Young.
We also acknowledge the following individuals for whose
assistance in the publication of this paper has been invaluable:
I. Kristo, A.E. Cottingham, S.A.O. Daida, C.R. Dulin, S.L.
Homola, L.L. Lucas, B.E. Moore, D.C. Verson, and J.F.
Vesecky.
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